Figs (FIGS) Operating Expenses (2020 - 2026)
Figs' Operating Expenses was $112.59 million in Q2 2026, up 21.9% from $92.33 million a year earlier and up 8.5% from the prior quarter.
Powered by 
Analysis
Figs (FIGS) Operating Expenses (2020 - 2026) Analysis & Trends
On a trailing twelve-month basis, Figs' Operating Expenses was $421.1 million through Jun 30, 2026, up 12.9% year-over-year; for FY2025, it was $381.69 million, up 2.2% from FY2024.
- Operating Expenses has now increased for six consecutive years, with a five-year compound annual growth rate of 23.6% (FY2020 to FY2025).
- In earlier years, Operating Expenses was $373.36 million in FY2024 (+8.9%), $342.92 million in FY2023 (+8.2%), $316.79 million in FY2022 (+9.1%) and $290.24 million in FY2021 (+119.4%).
- The Q2 2026 figure marks the highest quarterly Operating Expenses in data going back to Q2 2020.
- Compared with a year earlier, Operating Expenses has increased for three straight quarters, with growth averaging 10.5% over the last eight quarters.
- The best year-over-year quarter for Operating Expenses over five years was Q3 2021 (growth of 100.1%); the worst was Q2 2022 (a decline of 27.6%).
- Per Business Quant data, FIGS's Operating Expenses in the three quarters before Q2 2026 was $103.82 million (Q1 2026), $108.26 million (Q4 2025) and $96.43 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Nike | 56.18 Bn | 22.38 Bn | 4.80 Bn | 3.91 Bn |
| 2 | Tapestry | 23.99 Bn | 19.95 Bn | 1.56 Bn | 1.12 Bn |
| 3 | Ralph Lauren | 22.76 Bn | 14.85 Bn | 1.44 Bn | 1.10 Bn |
| 4 | Deckers Outdoor | 12.61 Bn | 5.48 Bn | - | - |
| 5 | Lululemon Athletica | 11.29 Bn | 5.54 Bn | 1.46 Bn | 1.01 Bn |
| 6 | Levi Strauss | 8.02 Bn | 4.60 Bn | 1.07 Bn | 843.50 Mn |
| 7 | V F | 6.86 Bn | 3.48 Bn | 917.04 Mn | 1.75 Bn |
| 8 | Gildan Activewear | 6.55 Bn | 5.47 Bn | 459.76 Mn | 283.86 Mn |
| 9 | Birkenstock Holding | 6.11 Bn | 4.43 Bn | 493.89 Mn | 37.80 Mn |
| 10 | Figs | 3.31 Bn | 2.20 Bn | 147.86 Mn | 112.59 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 112.59 Mn |
| Mar 31, 2026 | 103.82 Mn |
| Dec 31, 2025 | 108.26 Mn |
| Sep 30, 2025 | 96.43 Mn |
| Jun 30, 2025 | 92.33 Mn |
| Mar 31, 2025 | 84.67 Mn |
| Dec 31, 2024 | 93.30 Mn |
| Sep 30, 2024 | 102.66 Mn |
| Jun 30, 2024 | 95.71 Mn |
| Mar 31, 2024 | 81.69 Mn |
| Dec 31, 2023 | 83.63 Mn |
| Sep 30, 2023 | 87.44 Mn |
| Jun 30, 2023 | 89.47 Mn |
| Mar 31, 2023 | 82.38 Mn |
| Dec 31, 2022 | 95.59 Mn |
| Sep 30, 2022 | 79.62 Mn |
| Jun 30, 2022 | 76.90 Mn |
| Mar 31, 2022 | 64.69 Mn |
| Dec 31, 2021 | 73.57 Mn |
| Sep 30, 2021 | 64.15 Mn |
API Access
Figs Operating Expenses API
Pull this series into your own models, spreadsheets and apps with the Business Quant
Historical Metrics API. The request below matches the chart above — change the
frequency, period or values and it follows. Swap YOUR_API_KEY for your own key.
https://data.businessquant.com/historic?slug=operating-expenses&ticker=FIGS&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "FIGS", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=operating-expenses&ticker=FIGS&period=max&api_key=YOUR_API_KEY");
const data = await res.json();